The main expansion of the discovery of genetic variants associated with complex diseases has occurred during the last decade. This expansion has been accompanied, and in some sense motivated, by the desire to use this information to improve the predictive capacity of many diseases with an unidentified familial component, including coronary heart disease (CHD), with the aim of translating this genetic knowledge into clinical practice. This doctoral thesis is structured in two lines of investigation that address distinct aspects of this issue, first to evaluate the possible role of genetic variation in a candidate gene in modulating CHD risk, and second to evaluate whether genetic information can be used to improve risk assessment tools used in clinical practice.In the first research line (described in Part I), we investigate the contribution of genetic variation in one of the most widely-studied genes in cardiovascular genetics, ESR1, which encodes the Oestrogen receptor α protein. We provide a solid meta-analysis of evidence regarding the most widely-studied variant in this gene and we further explore the role of a broad range of common and uncommon variants in this gene in CHD risk. Using these approaches, we find no evidence of association between the genetic variants studied and CHD risk. However, although we can confidently accept that common genetic polymorphisms are not associated with cardiovascular disease, we cannot discard the possibility that other types of variation in this gene (for instance epigenetic variation) could modify susceptibility to cardiovascular disease, or that other elements of this pathway are associated with an increased risk of CHD. In this research I have provided a reliable answer to this long running unanswered question in cardiovascular genetics, allowing research to re-focus on other elements of this system or other pathways.In the second line, we explored the possible utility of genetic information obtained from genome-wide association studies (GWAS) in prediction of 10-year risk of CHD events by adding this information to cardiovascular risk functions. We have followed the recommendations proposed by the American Heart Association for evaluating the utility of novel biomarkers in clinical practice, and have demonstrated that although the magnitudes of the effects of these genetic variants on CHD risk are modest, there is a tendency towards improvement in the capacity of the risk functions to predict future CHD events. The translation of genetic information into clinical practice was one of the main motivations for the investment in genome-wide association studies, and my research represents one of the first efforts to explore this possibility.

Background: Altered DNA methylation has been associated with various diseases. Objective: We evaluated the association between levels of methylation in leukocyte DNA at long interspersed nuclear element 1 (LINE-1) and ...